{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:TSCPYMVGDLZ5CB5RYUWUUVPENV","short_pith_number":"pith:TSCPYMVG","canonical_record":{"source":{"id":"2605.19947","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T15:03:33Z","cross_cats_sorted":[],"title_canon_sha256":"15a365b685892f80ec510146aebfa0526fad86f7418308a817931bd32b8906b9","abstract_canon_sha256":"fea29f82aa7d9438decf6edd2d628a4f2da8324d9882ec8c3a95638c1183c893"},"schema_version":"1.0"},"canonical_sha256":"9c84fc32a61af3d107b1c52d4a55e46d73bf1c752910546d57140a12e4eb13c8","source":{"kind":"arxiv","id":"2605.19947","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.19947","created_at":"2026-05-20T02:05:56Z"},{"alias_kind":"arxiv_version","alias_value":"2605.19947v1","created_at":"2026-05-20T02:05:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.19947","created_at":"2026-05-20T02:05:56Z"},{"alias_kind":"pith_short_12","alias_value":"TSCPYMVGDLZ5","created_at":"2026-05-20T02:05:56Z"},{"alias_kind":"pith_short_16","alias_value":"TSCPYMVGDLZ5CB5R","created_at":"2026-05-20T02:05:56Z"},{"alias_kind":"pith_short_8","alias_value":"TSCPYMVG","created_at":"2026-05-20T02:05:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:TSCPYMVGDLZ5CB5RYUWUUVPENV","target":"record","payload":{"canonical_record":{"source":{"id":"2605.19947","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T15:03:33Z","cross_cats_sorted":[],"title_canon_sha256":"15a365b685892f80ec510146aebfa0526fad86f7418308a817931bd32b8906b9","abstract_canon_sha256":"fea29f82aa7d9438decf6edd2d628a4f2da8324d9882ec8c3a95638c1183c893"},"schema_version":"1.0"},"canonical_sha256":"9c84fc32a61af3d107b1c52d4a55e46d73bf1c752910546d57140a12e4eb13c8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T02:05:56.521685Z","signature_b64":"C6ua9N2P/JvuBSgfdkpTC7MQqiuWiYn8pj4yikyThTrVxMu8opCAjyey+4ogWxNkduB+vUSyR8goHWl1YhiUDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9c84fc32a61af3d107b1c52d4a55e46d73bf1c752910546d57140a12e4eb13c8","last_reissued_at":"2026-05-20T02:05:56.520895Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T02:05:56.520895Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.19947","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T02:05:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xW7IeKB/LiufytYLFTRDSkBojLeXDN2eOFWajhBn+ZzLcCxrnHNNevkhVs2+FOt7VHcSAEAC0/B7/7YCMvyWDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T18:16:01.343906Z"},"content_sha256":"d022da398d54e490cb74598cedb25b71bb175d8f3dbb882f1f12edb7bb37881e","schema_version":"1.0","event_id":"sha256:d022da398d54e490cb74598cedb25b71bb175d8f3dbb882f1f12edb7bb37881e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:TSCPYMVGDLZ5CB5RYUWUUVPENV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploiting Non-Negativity in DAG Structure Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Gonzalo Mateos, Madeline Navarro, Samuel Rey","submitted_at":"2026-05-19T15:03:33Z","abstract_excerpt":"This work addresses the problem of learning directed acyclic graphs (DAGs) from nodal observations generated by a linear structural equation model. DAG learning is a central task in signal processing, machine learning, and causal inference, but it remains challenging because acyclicity is a global combinatorial property. Continuous acyclicity constraints have led to important algorithmic advances by replacing the discrete DAG constraint with smooth equality constraints. However, existing formulations still involve difficult non-convex optimization landscapes and may suffer from degenerate firs"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.19947","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.19947/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T02:05:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"55oIlEVUqS2+6RmC23gwOnjldHdKGQFOMaYGi01JqhJh6FkjYbRwvYqm+wVvnAQz16OaHahEwL9IfCfXDbrhCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-21T18:16:01.344283Z"},"content_sha256":"b0000a14430ef429787e38147ce119b4cf9a4e571dabecd58aa4c7b48ca43ecd","schema_version":"1.0","event_id":"sha256:b0000a14430ef429787e38147ce119b4cf9a4e571dabecd58aa4c7b48ca43ecd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TSCPYMVGDLZ5CB5RYUWUUVPENV/bundle.json","state_url":"https://pith.science/pith/TSCPYMVGDLZ5CB5RYUWUUVPENV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TSCPYMVGDLZ5CB5RYUWUUVPENV/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-21T18:16:01Z","links":{"resolver":"https://pith.science/pith/TSCPYMVGDLZ5CB5RYUWUUVPENV","bundle":"https://pith.science/pith/TSCPYMVGDLZ5CB5RYUWUUVPENV/bundle.json","state":"https://pith.science/pith/TSCPYMVGDLZ5CB5RYUWUUVPENV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TSCPYMVGDLZ5CB5RYUWUUVPENV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:TSCPYMVGDLZ5CB5RYUWUUVPENV","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"fea29f82aa7d9438decf6edd2d628a4f2da8324d9882ec8c3a95638c1183c893","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T15:03:33Z","title_canon_sha256":"15a365b685892f80ec510146aebfa0526fad86f7418308a817931bd32b8906b9"},"schema_version":"1.0","source":{"id":"2605.19947","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.19947","created_at":"2026-05-20T02:05:56Z"},{"alias_kind":"arxiv_version","alias_value":"2605.19947v1","created_at":"2026-05-20T02:05:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.19947","created_at":"2026-05-20T02:05:56Z"},{"alias_kind":"pith_short_12","alias_value":"TSCPYMVGDLZ5","created_at":"2026-05-20T02:05:56Z"},{"alias_kind":"pith_short_16","alias_value":"TSCPYMVGDLZ5CB5R","created_at":"2026-05-20T02:05:56Z"},{"alias_kind":"pith_short_8","alias_value":"TSCPYMVG","created_at":"2026-05-20T02:05:56Z"}],"graph_snapshots":[{"event_id":"sha256:b0000a14430ef429787e38147ce119b4cf9a4e571dabecd58aa4c7b48ca43ecd","target":"graph","created_at":"2026-05-20T02:05:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2605.19947/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This work addresses the problem of learning directed acyclic graphs (DAGs) from nodal observations generated by a linear structural equation model. DAG learning is a central task in signal processing, machine learning, and causal inference, but it remains challenging because acyclicity is a global combinatorial property. Continuous acyclicity constraints have led to important algorithmic advances by replacing the discrete DAG constraint with smooth equality constraints. However, existing formulations still involve difficult non-convex optimization landscapes and may suffer from degenerate firs","authors_text":"Gonzalo Mateos, Madeline Navarro, Samuel Rey","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T15:03:33Z","title":"Exploiting Non-Negativity in DAG Structure Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.19947","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:d022da398d54e490cb74598cedb25b71bb175d8f3dbb882f1f12edb7bb37881e","target":"record","created_at":"2026-05-20T02:05:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"fea29f82aa7d9438decf6edd2d628a4f2da8324d9882ec8c3a95638c1183c893","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-19T15:03:33Z","title_canon_sha256":"15a365b685892f80ec510146aebfa0526fad86f7418308a817931bd32b8906b9"},"schema_version":"1.0","source":{"id":"2605.19947","kind":"arxiv","version":1}},"canonical_sha256":"9c84fc32a61af3d107b1c52d4a55e46d73bf1c752910546d57140a12e4eb13c8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9c84fc32a61af3d107b1c52d4a55e46d73bf1c752910546d57140a12e4eb13c8","first_computed_at":"2026-05-20T02:05:56.520895Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T02:05:56.520895Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"C6ua9N2P/JvuBSgfdkpTC7MQqiuWiYn8pj4yikyThTrVxMu8opCAjyey+4ogWxNkduB+vUSyR8goHWl1YhiUDg==","signature_status":"signed_v1","signed_at":"2026-05-20T02:05:56.521685Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.19947","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d022da398d54e490cb74598cedb25b71bb175d8f3dbb882f1f12edb7bb37881e","sha256:b0000a14430ef429787e38147ce119b4cf9a4e571dabecd58aa4c7b48ca43ecd"],"state_sha256":"8b0d0459d74e79bdb010a05884c6b31cc46f67f577d6883d8617bac7a9ce925c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"an07XjwRPOplSgVq5FJICowfqTOGPpXg2QBU0YKe8cKPmrksV3KpdeWTa7eFtkp+DgWYOCg8qE6YaH6zRLAsDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-21T18:16:01.346567Z","bundle_sha256":"af17ee454859510e81a9d2a8cc4a2c4aba4550bee2163d098ce400b0fcc5e17a"}}